#library to work with data
import pandas as pd
#Library to plot matrices
import numpy as np
import matplotlib . pyplot as plt
import seaborn as sns ; sns . set()
import plotly.express as px
#import geopandas as gpd
import folium
from plotly.offline import plot
import plotly.graph_objects as go
%matplotlib inline
%matplotlib notebook
from IPython.display import Latex
#plotly.offline.init_notebook_mode(connected=True)
#plotly.offline.(i)plot
import plotly.io as pio
pio.renderers.default='notebook'
#Load Data
confirmed = pd. read_csv("G:/My Drive/UPITT/Capstone/Data/covid_confirmed_usafacts.csv")
deaths = pd. read_csv("G:/My Drive/UPITT/Capstone/Data/covid_deaths_usafacts.csv")
vaccine = pd. read_csv("G:/My Drive/UPITT/Capstone/Data/COVID19_CDC_Vaccination_CSV_Download.csv")
#confirmed.head()
#confirmed.tail()
#deaths.tail()
print(confirmed.shape)
print(deaths.shape)
print(vaccine.shape)
(3193, 775) (3193, 775) (50209, 14)
#Checking for missing values
#confirmed.isnull().sum()
#Checking for missing values
#deaths.isnull().sum()
#Drop Columns
confirmed_df = confirmed.drop(columns=["countyFIPS", "County Name","StateFIPS"])
death_df = deaths.drop(columns=["countyFIPS", "County Name","StateFIPS"])
#Group by State
confirmed_df = confirmed_df.groupby(by="State").aggregate(np.sum).T
death_df = death_df.groupby(by="State").aggregate(np.sum).T
confirmed_df.head()
| State | AK | AL | AR | AZ | CA | CO | CT | DC | DE | FL | ... | SD | TN | TX | UT | VA | VT | WA | WI | WV | WY |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-01-22 | 0 | 0 | 0 | 0 | 722 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 2020-01-23 | 0 | 0 | 0 | 0 | 733 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 2020-01-24 | 0 | 0 | 0 | 0 | 739 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 2020-01-25 | 0 | 0 | 0 | 0 | 749 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 2020-01-26 | 0 | 0 | 0 | 1 | 756 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
5 rows × 51 columns
death_df.head()
| State | AK | AL | AR | AZ | CA | CO | CT | DC | DE | FL | ... | SD | TN | TX | UT | VA | VT | WA | WI | WV | WY |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-01-22 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| 2020-01-23 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| 2020-01-24 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| 2020-01-25 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| 2020-01-26 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
5 rows × 51 columns
confirmed_df.index.name='Date'
confirmed_df = confirmed_df.reset_index()
confirmed_df.head()
| State | Date | AK | AL | AR | AZ | CA | CO | CT | DC | DE | ... | SD | TN | TX | UT | VA | VT | WA | WI | WV | WY |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2020-01-22 | 0 | 0 | 0 | 0 | 722 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 1 | 2020-01-23 | 0 | 0 | 0 | 0 | 733 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 2 | 2020-01-24 | 0 | 0 | 0 | 0 | 739 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 3 | 2020-01-25 | 0 | 0 | 0 | 0 | 749 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 4 | 2020-01-26 | 0 | 0 | 0 | 1 | 756 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
5 rows × 52 columns
death_df.index.name='Date'
death_df = death_df.reset_index()
death_df.head()
| State | Date | AK | AL | AR | AZ | CA | CO | CT | DC | DE | ... | SD | TN | TX | UT | VA | VT | WA | WI | WV | WY |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2020-01-22 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| 1 | 2020-01-23 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| 2 | 2020-01-24 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| 3 | 2020-01-25 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| 4 | 2020-01-26 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
5 rows × 52 columns
#Change dataframe from wide to long format
confirmed_melt_df = confirmed_df.melt(id_vars='Date').copy()
death_melt_df = death_df.melt(id_vars='Date').copy()
confirmed_melt_df
| Date | State | value | |
|---|---|---|---|
| 0 | 2020-01-22 | AK | 0 |
| 1 | 2020-01-23 | AK | 0 |
| 2 | 2020-01-24 | AK | 0 |
| 3 | 2020-01-25 | AK | 0 |
| 4 | 2020-01-26 | AK | 0 |
| ... | ... | ... | ... |
| 39316 | 2022-02-26 | WY | 154549 |
| 39317 | 2022-02-27 | WY | 154549 |
| 39318 | 2022-02-28 | WY | 154909 |
| 39319 | 2022-03-01 | WY | 154909 |
| 39320 | 2022-03-02 | WY | 154909 |
39321 rows × 3 columns
death_melt_df
| Date | State | value | |
|---|---|---|---|
| 0 | 2020-01-22 | AK | 0 |
| 1 | 2020-01-23 | AK | 0 |
| 2 | 2020-01-24 | AK | 0 |
| 3 | 2020-01-25 | AK | 0 |
| 4 | 2020-01-26 | AK | 0 |
| ... | ... | ... | ... |
| 39316 | 2022-02-26 | WY | 1718 |
| 39317 | 2022-02-27 | WY | 1718 |
| 39318 | 2022-02-28 | WY | 1718 |
| 39319 | 2022-03-01 | WY | 1741 |
| 39320 | 2022-03-02 | WY | 1741 |
39321 rows × 3 columns
confirmed_melt_df.rename(columns={'value':'Cases'}, inplace=True)
death_melt_df.rename(columns={'value':'Deaths'}, inplace=True)
confirmed_melt_df.head()
| Date | State | Cases | |
|---|---|---|---|
| 0 | 2020-01-22 | AK | 0 |
| 1 | 2020-01-23 | AK | 0 |
| 2 | 2020-01-24 | AK | 0 |
| 3 | 2020-01-25 | AK | 0 |
| 4 | 2020-01-26 | AK | 0 |
death_melt_df.head()
| Date | State | Deaths | |
|---|---|---|---|
| 0 | 2020-01-22 | AK | 0 |
| 1 | 2020-01-23 | AK | 0 |
| 2 | 2020-01-24 | AK | 0 |
| 3 | 2020-01-25 | AK | 0 |
| 4 | 2020-01-26 | AK | 0 |
max_date = confirmed_melt_df['Date'].max()
max_date
max_date1 = death_melt_df['Date'].max()
max_date1
'2022-03-02'
confirmed_melt_df['Date'] = pd.to_datetime(confirmed_melt_df['Date'])
death_melt_df['Date'] = pd.to_datetime(death_melt_df['Date'])
confirmed_melt_df.head()
| Date | State | Cases | |
|---|---|---|---|
| 0 | 2020-01-22 | AK | 0 |
| 1 | 2020-01-23 | AK | 0 |
| 2 | 2020-01-24 | AK | 0 |
| 3 | 2020-01-25 | AK | 0 |
| 4 | 2020-01-26 | AK | 0 |
death_melt_df.head()
| Date | State | Deaths | |
|---|---|---|---|
| 0 | 2020-01-22 | AK | 0 |
| 1 | 2020-01-23 | AK | 0 |
| 2 | 2020-01-24 | AK | 0 |
| 3 | 2020-01-25 | AK | 0 |
| 4 | 2020-01-26 | AK | 0 |
confirmed_melt_df['Date'] = confirmed_melt_df['Date'].dt.strftime('%m/%d/%Y')
death_melt_df['Date'] = death_melt_df['Date'].dt.strftime('%m/%d/%Y')
max_date = confirmed_melt_df['Date'].max()
max_date
max_date1 = confirmed_melt_df['Date'].max()
max_date1
'12/31/2021'
total_confirmed_df = confirmed_melt_df[confirmed_melt_df['Date'] == max_date]
total_death_df = death_melt_df[death_melt_df['Date'] == max_date]
total_confirmed_df
| Date | State | Cases | |
|---|---|---|---|
| 709 | 12/31/2021 | AK | 149907 |
| 1480 | 12/31/2021 | AL | 896614 |
| 2251 | 12/31/2021 | AR | 562455 |
| 3022 | 12/31/2021 | AZ | 1381488 |
| 3793 | 12/31/2021 | CA | 5397950 |
| 4564 | 12/31/2021 | CO | 954170 |
| 5335 | 12/31/2021 | CT | 510188 |
| 6106 | 12/31/2021 | DC | 94286 |
| 6877 | 12/31/2021 | DE | 180366 |
| 7648 | 12/31/2021 | FL | 4222899 |
| 8419 | 12/31/2021 | GA | 1420034 |
| 9190 | 12/31/2021 | HI | 112932 |
| 9961 | 12/31/2021 | IA | 582348 |
| 10732 | 12/31/2021 | ID | 319382 |
| 11503 | 12/31/2021 | IL | 2181031 |
| 12274 | 12/31/2021 | IN | 1250836 |
| 13045 | 12/31/2021 | KS | 519544 |
| 13816 | 12/31/2021 | KY | 856145 |
| 14587 | 12/31/2021 | LA | 828695 |
| 15358 | 12/31/2021 | MA | 1060110 |
| 16129 | 12/31/2021 | MD | 726388 |
| 16900 | 12/31/2021 | ME | 146736 |
| 17671 | 12/31/2021 | MI | 1710277 |
| 18442 | 12/31/2021 | MN | 1022212 |
| 19213 | 12/31/2021 | MO | 1006913 |
| 19984 | 12/31/2021 | MS | 543737 |
| 20755 | 12/31/2021 | MT | 197724 |
| 21526 | 12/31/2021 | NC | 1667493 |
| 22297 | 12/31/2021 | ND | 173379 |
| 23068 | 12/31/2021 | NE | 342939 |
| 23839 | 12/31/2021 | NH | 198667 |
| 24610 | 12/31/2021 | NJ | 1564253 |
| 25381 | 12/31/2021 | NM | 350043 |
| 26152 | 12/31/2021 | NV | 501181 |
| 26923 | 12/31/2021 | NY | 3469564 |
| 27694 | 12/31/2021 | OH | 2016095 |
| 28465 | 12/31/2021 | OK | 708938 |
| 29236 | 12/31/2021 | OR | 421265 |
| 30007 | 12/31/2021 | PA | 2036424 |
| 30778 | 12/31/2021 | RI | 231096 |
| 31549 | 12/31/2021 | SC | 975320 |
| 32320 | 12/31/2021 | SD | 178395 |
| 33091 | 12/31/2021 | TN | 1412302 |
| 33862 | 12/31/2021 | TX | 4572523 |
| 34633 | 12/31/2021 | UT | 636992 |
| 35404 | 12/31/2021 | VA | 1118518 |
| 36175 | 12/31/2021 | VT | 64447 |
| 36946 | 12/31/2021 | WA | 849075 |
| 37717 | 12/31/2021 | WI | 1120663 |
| 38488 | 12/31/2021 | WV | 328162 |
| 39259 | 12/31/2021 | WY | 115638 |
total_death_df
| Date | State | Deaths | |
|---|---|---|---|
| 709 | 12/31/2021 | AK | 938 |
| 1480 | 12/31/2021 | AL | 16455 |
| 2251 | 12/31/2021 | AR | 9148 |
| 3022 | 12/31/2021 | AZ | 24229 |
| 3793 | 12/31/2021 | CA | 75656 |
| 4564 | 12/31/2021 | CO | 10322 |
| 5335 | 12/31/2021 | CT | 9160 |
| 6106 | 12/31/2021 | DC | 1211 |
| 6877 | 12/31/2021 | DE | 2286 |
| 7648 | 12/31/2021 | FL | 62539 |
| 8419 | 12/31/2021 | GA | 31443 |
| 9190 | 12/31/2021 | HI | 1090 |
| 9961 | 12/31/2021 | IA | 7858 |
| 10732 | 12/31/2021 | ID | 4162 |
| 11503 | 12/31/2021 | IL | 31017 |
| 12274 | 12/31/2021 | IN | 19037 |
| 13045 | 12/31/2021 | KS | 6673 |
| 13816 | 12/31/2021 | KY | 12118 |
| 14587 | 12/31/2021 | LA | 14986 |
| 15358 | 12/31/2021 | MA | 20273 |
| 16129 | 12/31/2021 | MD | 11758 |
| 16900 | 12/31/2021 | ME | 1531 |
| 17671 | 12/31/2021 | MI | 29019 |
| 18442 | 12/31/2021 | MN | 10516 |
| 19213 | 12/31/2021 | MO | 16074 |
| 19984 | 12/31/2021 | MS | 10450 |
| 20755 | 12/31/2021 | MT | 2906 |
| 21526 | 12/31/2021 | NC | 19399 |
| 22297 | 12/31/2021 | ND | 2007 |
| 23068 | 12/31/2021 | NE | 3341 |
| 23839 | 12/31/2021 | NH | 1961 |
| 24610 | 12/31/2021 | NJ | 29037 |
| 25381 | 12/31/2021 | NM | 5855 |
| 26152 | 12/31/2021 | NV | 8420 |
| 26923 | 12/31/2021 | NY | 59289 |
| 27694 | 12/31/2021 | OH | 29447 |
| 28465 | 12/31/2021 | OK | 11851 |
| 29236 | 12/31/2021 | OR | 5655 |
| 30007 | 12/31/2021 | PA | 36705 |
| 30778 | 12/31/2021 | RI | 3066 |
| 31549 | 12/31/2021 | SC | 14636 |
| 32320 | 12/31/2021 | SD | 2474 |
| 33091 | 12/31/2021 | TN | 20851 |
| 33862 | 12/31/2021 | TX | 74778 |
| 34633 | 12/31/2021 | UT | 3787 |
| 35404 | 12/31/2021 | VA | 15587 |
| 36175 | 12/31/2021 | VT | 471 |
| 36946 | 12/31/2021 | WA | 9853 |
| 37717 | 12/31/2021 | WI | 11173 |
| 38488 | 12/31/2021 | WV | 5336 |
| 39259 | 12/31/2021 | WY | 1526 |
total_confirmed = total_confirmed_df['Cases'].sum()
print(total_confirmed)
total_death = total_death_df['Deaths'].sum()
print(total_death)
53888739 819360
fig1 = px.bar(total_confirmed_df, x='State', y='Cases', title='Total Confirmed Cases')
fig1.show()
fig1_1 = px.bar(total_death_df, x='State', y='Deaths', title='Total Death Cases')
fig1_1.show()
fig2 = px.bar(total_confirmed_df.sort_values('Cases', ascending=False).head(50),
x='State', y='Cases', text='Cases', title='Total Confirmed Cases')
fig2.show()
fig2_1 = px.bar(total_death_df.sort_values('Deaths', ascending=False).head(50),
x='State', y='Deaths', text='Deaths', title='Total Death Cases')
fig2_1.show()
fig = px.line(confirmed_melt_df, x="Date", y="Cases", color='State', title='Total Confirmed Cases')
fig.show()
fig = px.line(death_melt_df, x="Date", y="Deaths", color='State', title='Total Death Cases')
fig.show()
fig4 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'AK'], x='Date', y='Cases', title='AK Covid Cases')
fig4.show()
fig4_1 = px.line(death_melt_df[death_melt_df['State'] == 'AK'], x='Date', y='Deaths', title='AK Death Cases')
fig4_1.show()
fig5 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'AL'], x='Date', y='Cases', title='AL Covid Cases')
fig5.show()
fig5_1 = px.line(death_melt_df[death_melt_df['State'] == 'AL'], x='Date', y='Deaths', title='AL Death Cases')
fig5_1.show()
fig6 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'AR'], x='Date', y='Cases', title='AR Covid Cases')
fig6.show()
fig6_1 = px.line(death_melt_df[death_melt_df['State'] == 'AR'], x='Date', y='Deaths', title='AR Death Cases')
fig6_1.show()
fig7 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'AZ'], x='Date', y='Cases', title='AZ Covid Cases')
fig7.show()
fig7_1 = px.line(death_melt_df[death_melt_df['State'] == 'AZ'], x='Date', y='Deaths', title='AZ Death Cases')
fig7_1.show()
fig8 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'CA'], x='Date', y='Cases', title='CA Covid Cases')
fig8.show()
fig8_1 = px.line(death_melt_df[death_melt_df['State'] == 'CA'], x='Date', y='Deaths', title='CA Death Cases')
fig8_1.show()
fig9 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'CO'], x='Date', y='Cases', title='CO Confirmed Cases')
fig9.show()
fig9_1 = px.line(death_melt_df[death_melt_df['State'] == 'CO'], x='Date', y='Deaths', title='CO Death Cases')
fig9_1.show()
fig10 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'CT'], x='Date', y='Cases', title='CT Covid Cases')
fig10.show()
fig10_1 = px.line(death_melt_df[death_melt_df['State'] == 'CT'], x='Date', y='Deaths', title='CT Death Cases')
fig10_1.show()
fig11 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'DC'], x='Date', y='Cases', title='DC Covid Cases')
fig11.show()
fig11_1 = px.line(death_melt_df[death_melt_df['State'] == 'DC'], x='Date', y='Deaths', title='DC Death Cases')
fig11_1.show()
fig12 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'DE'], x='Date', y='Cases', title='DE Covid Cases')
fig12.show()
fig12_1 = px.line(death_melt_df[death_melt_df['State'] == 'DE'], x='Date', y='Deaths', title='DE Death Cases')
fig4_1.show()
fig13 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'FL'], x='Date', y='Cases', title='FL Covid Cases')
fig13.show()
fig13_1 = px.line(death_melt_df[death_melt_df['State'] == 'FL'], x='Date', y='Deaths', title='FL Death Cases')
fig13_1.show()
fig14 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'GA'], x='Date', y='Cases', title='GA Covid Cases')
fig14.show()
fig14_1 = px.line(death_melt_df[death_melt_df['State'] == 'GA'], x='Date', y='Deaths', title='GA Death Cases')
fig14_1.show()
fig15 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'HI'], x='Date', y='Cases', title='HI Covid Cases')
fig15.show()
fig15_1 = px.line(death_melt_df[death_melt_df['State'] == 'HI'], x='Date', y='Deaths', title='HI Death Cases')
fig15_1.show()
fig16 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'IA'], x='Date', y='Cases', title='IA Covid Cases')
fig16.show()
fig16_1 = px.line(death_melt_df[death_melt_df['State'] == 'IA'], x='Date', y='Deaths', title='IA Death Cases')
fig16_1.show()
fig17 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'ID'], x='Date', y='Cases', title='ID Covid Cases')
fig17.show()
fig17_1 = px.line(death_melt_df[death_melt_df['State'] == 'ID'], x='Date', y='Deaths', title='ID Death Cases')
fig17_1.show()
fig18 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'IL'], x='Date', y='Cases', title='IL Covid Cases')
fig18.show()
fig18_1 = px.line(death_melt_df[death_melt_df['State'] == 'IL'], x='Date', y='Deaths', title='IL Death Cases')
fig18_1.show()
fig19 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'IN'], x='Date', y='Cases', title='IN Covid Cases')
fig19.show()
fig19_1 = px.line(death_melt_df[death_melt_df['State'] == 'IN'], x='Date', y='Deaths', title='IN Death Cases')
fig19_1.show()
fig20 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'KS'], x='Date', y='Cases', title='KS Covid Cases')
fig20.show()
fig20_1 = px.line(death_melt_df[death_melt_df['State'] == 'KS'], x='Date', y='Deaths', title='KS Death Cases')
fig20_1.show()
fig21 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'KY'], x='Date', y='Cases', title='KY Covid Cases')
fig21.show()
fig21_1 = px.line(death_melt_df[death_melt_df['State'] == 'KY'], x='Date', y='Deaths', title='KY Death Cases')
fig21_1.show()
fig22 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'LA'], x='Date', y='Cases', title='LA Covid Cases')
fig22.show()
fig22_1 = px.line(death_melt_df[death_melt_df['State'] == 'LA'], x='Date', y='Deaths', title='LA Death Cases')
fig22_1.show()
fig23 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'MA'], x='Date', y='Cases', title='MA Covid Cases')
fig23.show()
fig23_1 = px.line(death_melt_df[death_melt_df['State'] == 'MA'], x='Date', y='Deaths', title='MA Death Cases')
fig23_1.show()
fig24 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'MD'], x='Date', y='Cases', title='MD Covid Cases')
fig24.show()
fig24_1 = px.line(death_melt_df[death_melt_df['State'] == 'MD'], x='Date', y='Deaths', title='MD Death Cases')
fig24_1.show()
fig25 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'ME'], x='Date', y='Cases', title='ME Covid Cases')
fig25.show()
fig25_1 = px.line(death_melt_df[death_melt_df['State'] == 'ME'], x='Date', y='Deaths', title='ME Death Cases')
fig25_1.show()
fig26 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'MI'], x='Date', y='Cases', title='MI Covid Cases')
fig26.show()
fig26_1 = px.line(death_melt_df[death_melt_df['State'] == 'MI'], x='Date', y='Deaths', title='MI Death Cases')
fig26_1.show()
fig27 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'MN'], x='Date', y='Cases', title='MN Covid Cases')
fig27.show()
fig27_1 = px.line(death_melt_df[death_melt_df['State'] == 'MN'], x='Date', y='Deaths', title='MN Death Cases')
fig27_1.show()
fig28 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'MO'], x='Date', y='Cases', title='MO Covid Cases')
fig28.show()
fig28_1 = px.line(death_melt_df[death_melt_df['State'] == 'MO'], x='Date', y='Deaths', title='MO Death Cases')
fig28_1.show()
fig29 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'MS'], x='Date', y='Cases', title='MS Covid Cases')
fig29.show()
fig29_1 = px.line(death_melt_df[death_melt_df['State'] == 'MS'], x='Date', y='Deaths', title='MS Death Cases')
fig29_1.show()
fig30 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'MT'], x='Date', y='Cases', title='MT Covid Cases')
fig30.show()
fig30_1 = px.line(death_melt_df[death_melt_df['State'] == 'MT'], x='Date', y='Deaths', title='MT Death Cases')
fig30_1.show()
fig31 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'NC'], x='Date', y='Cases', title='NC Covid Cases')
fig31.show()
fig31_1 = px.line(death_melt_df[death_melt_df['State'] == 'NC'], x='Date', y='Deaths', title='NC Death Cases')
fig31_1.show()
fig32 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'ND'], x='Date', y='Cases', title='ND Covid Cases')
fig32.show()
fig32_1 = px.line(death_melt_df[death_melt_df['State'] == 'ND'], x='Date', y='Deaths', title='ND Death Cases')
fig32_1.show()
fig33 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'NE'], x='Date', y='Cases', title='NE Covid Cases')
fig33.show()
fig33_1 = px.line(death_melt_df[death_melt_df['State'] == 'NE'], x='Date', y='Deaths', title='NE Death Cases')
fig33_1.show()
fig34 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'NH'], x='Date', y='Cases', title='NH Covid Cases')
fig34.show()
fig34_1 = px.line(death_melt_df[death_melt_df['State'] == 'NH'], x='Date', y='Deaths', title='NH Death Cases')
fig34_1.show()
fig35 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'NJ'], x='Date', y='Cases', title='NJ Covid Cases')
fig35.show()
fig35_1 = px.line(death_melt_df[death_melt_df['State'] == 'NJ'], x='Date', y='Deaths', title='NJ Death Cases')
fig35_1.show()
fig36 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'NM'], x='Date', y='Cases', title='NM Covid Cases')
fig36.show()
fig36_1 = px.line(death_melt_df[death_melt_df['State'] == 'NM'], x='Date', y='Deaths', title='NM Death Cases')
fig36_1.show()
fig37 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'NV'], x='Date', y='Cases', title='NV Covid Cases')
fig37.show()
fig37_1 = px.line(death_melt_df[death_melt_df['State'] == 'NV'], x='Date', y='Deaths', title='NV Death Cases')
fig37_1.show()
fig38 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'NY'], x='Date', y='Cases', title='NY Covid Cases')
fig38.show()
fig38_1 = px.line(death_melt_df[death_melt_df['State'] == 'NY'], x='Date', y='Deaths', title='NY Death Cases')
fig38_1.show()
fig39 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'OH'], x='Date', y='Cases', title='OH Covid Cases')
fig39.show()
fig39_1 = px.line(death_melt_df[death_melt_df['State'] == 'OH'], x='Date', y='Deaths', title='OH Death Cases')
fig39_1.show()
fig40 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'OK'], x='Date', y='Cases', title='OK Covid Cases')
fig40.show()
fig40_1 = px.line(death_melt_df[death_melt_df['State'] == 'OK'], x='Date', y='Deaths', title='OK Death Cases')
fig40_1.show()
fig41 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'OR'], x='Date', y='Cases', title='OR Covid Cases')
fig41.show()
fig41_1 = px.line(death_melt_df[death_melt_df['State'] == 'OR'], x='Date', y='Deaths', title='OR Death Cases')
fig41_1.show()
fig42 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'PA'], x='Date', y='Cases', title='PA Covid Cases')
fig42.show()
fig42_1 = px.line(death_melt_df[death_melt_df['State'] == 'PA'], x='Date', y='Deaths', title='PA Death Cases')
fig42_1.show()
fig43 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'RI'], x='Date', y='Cases', title='RI Covid Cases')
fig43.show()
fig43_1 = px.line(death_melt_df[death_melt_df['State'] == 'RI'], x='Date', y='Deaths', title='RI Death Cases')
fig43_1.show()
fig44 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'SC'], x='Date', y='Cases', title='SC Covid Cases')
fig44.show()
fig44_1 = px.line(death_melt_df[death_melt_df['State'] == 'SC'], x='Date', y='Deaths', title='SC Death Cases')
fig44_1.show()
fig45 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'SD'], x='Date', y='Cases', title='SD Covid Cases')
fig45.show()
fig45_1 = px.line(death_melt_df[death_melt_df['State'] == 'SD'], x='Date', y='Deaths', title='SD Death Cases')
fig45_1.show()
fig46 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'TN'], x='Date', y='Cases', title='TN Covid Cases')
fig46.show()
fig46_1 = px.line(death_melt_df[death_melt_df['State'] == 'TN'], x='Date', y='Deaths', title='TN Death Cases')
fig46_1.show()
fig47 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'TX'], x='Date', y='Cases', title='TX Covid Cases')
fig47.show()
fig47_1 = px.line(death_melt_df[death_melt_df['State'] == 'TX'], x='Date', y='Deaths', title='TX Death Cases')
fig47_1.show()
fig48 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'UT'], x='Date', y='Cases', title='UT Covid Cases')
fig48.show()
fig48_1 = px.line(death_melt_df[death_melt_df['State'] == 'UT'], x='Date', y='Deaths', title='UT Death Cases')
fig48_1.show()
fig49 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'VA'], x='Date', y='Cases', title='VA Covid Cases')
fig48.show()
fig49_1 = px.line(death_melt_df[death_melt_df['State'] == 'VA'], x='Date', y='Deaths', title='VA Death Cases')
fig49_1.show()
fig50 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'VT'], x='Date', y='Cases', title='VT Covid Cases')
fig50.show()
fig50_1 = px.line(death_melt_df[death_melt_df['State'] == 'VT'], x='Date', y='Deaths', title='VT Death Cases')
fig50_1.show()
fig51 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'WA'], x='Date', y='Cases', title='WA Covid Cases')
fig51.show()
fig51_1 = px.line(death_melt_df[death_melt_df['State'] == 'WA'], x='Date', y='Deaths', title='WA Death Cases')
fig51_1.show()
fig52 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'WI'], x='Date', y='Cases', title='WI Covid Cases')
fig52.show()
fig52_1 = px.line(death_melt_df[death_melt_df['State'] == 'WI'], x='Date', y='Deaths', title='WI Death Cases')
fig52_1.show()
fig53 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'WV'], x='Date', y='Cases', title='WV Covid Cases')
fig53.show()
fig53_1 = px.line(death_melt_df[death_melt_df['State'] == 'WV'], x='Date', y='Deaths', title='WV Death Cases')
fig53_1.show()
fig54 = px.line(confirmed_melt_df[confirmed_melt_df['State'] == 'WY'], x='Date', y='Cases', title='WY Covid Cases')
fig54.show()
fig54_1 = px.line(death_melt_df[death_melt_df['State'] == 'WY'], x='Date', y='Deaths', title='WY Death Cases')
fig54_1.show()
confirmed_melt_df['Date'] = pd.to_datetime(confirmed_melt_df['Date'], errors='coerce')
death_melt_df['Date'] = pd.to_datetime(death_melt_df['Date'], errors='coerce')
c_df = (confirmed_melt_df.groupby([pd.Grouper(key='Date', freq='MS'), 'State'])['Cases']
.sum()
.reset_index())
d_df = (death_melt_df.groupby([pd.Grouper(key='Date', freq='MS'), 'State'])['Deaths']
.sum()
.reset_index())
c_df.head()
| Date | State | Cases | |
|---|---|---|---|
| 0 | 2020-01-01 | AK | 0 |
| 1 | 2020-01-01 | AL | 0 |
| 2 | 2020-01-01 | AR | 0 |
| 3 | 2020-01-01 | AZ | 6 |
| 4 | 2020-01-01 | CA | 7594 |
d_df.head()
| Date | State | Deaths | |
|---|---|---|---|
| 0 | 2020-01-01 | AK | 0 |
| 1 | 2020-01-01 | AL | 0 |
| 2 | 2020-01-01 | AR | 0 |
| 3 | 2020-01-01 | AZ | 0 |
| 4 | 2020-01-01 | CA | 0 |
#Create Month and Year Column
c_df['month'] = c_df['Date'].dt.month
d_df['month'] = d_df['Date'].dt.month
c_df['year'] = c_df['Date'].dt.year
d_df['year'] = d_df['Date'].dt.year
c_df
| Date | State | Cases | month | year | |
|---|---|---|---|---|---|
| 0 | 2020-01-01 | AK | 0 | 1 | 2020 |
| 1 | 2020-01-01 | AL | 0 | 1 | 2020 |
| 2 | 2020-01-01 | AR | 0 | 1 | 2020 |
| 3 | 2020-01-01 | AZ | 6 | 1 | 2020 |
| 4 | 2020-01-01 | CA | 7594 | 1 | 2020 |
| ... | ... | ... | ... | ... | ... |
| 1372 | 2022-03-01 | VT | 225456 | 3 | 2022 |
| 1373 | 2022-03-01 | WA | 2851003 | 3 | 2022 |
| 1374 | 2022-03-01 | WI | 3146145 | 3 | 2022 |
| 1375 | 2022-03-01 | WV | 981586 | 3 | 2022 |
| 1376 | 2022-03-01 | WY | 309818 | 3 | 2022 |
1377 rows × 5 columns
#Rename Month and Year Rows
c_df['month'] = c_df['month'].replace({1: 'Jan', 2: 'Feb', 3: 'Mar', 4: 'Apr', 5: 'May', 6: 'Jun', 7: 'Jul', 8: 'Aug', 9: 'Sep', 10: 'Oct', 11: 'Nov', 12: 'Dec'})
d_df['month'] = d_df['month'].replace({1: 'Jan', 2: 'Feb', 3: 'Mar', 4: 'Apr', 5: 'May', 6: 'Jun', 7: 'Jul', 8: 'Aug', 9: 'Sep', 10: 'Oct', 11: 'Nov', 12: 'Dec'})
c_df.head()
| Date | State | Cases | month | year | |
|---|---|---|---|---|---|
| 0 | 2020-01-01 | AK | 0 | Jan | 2020 |
| 1 | 2020-01-01 | AL | 0 | Jan | 2020 |
| 2 | 2020-01-01 | AR | 0 | Jan | 2020 |
| 3 | 2020-01-01 | AZ | 6 | Jan | 2020 |
| 4 | 2020-01-01 | CA | 7594 | Jan | 2020 |
#early = c_df.loc[c_df['State'].isin(['AL','AK','AZ','AR','FL','GA','ID','IN','IA','MD','MS','MO','NE','NH','ND','OH','OK','SC','TN','TX','UT','WV','WY'])
#Select Rows
c_early = c_df[c_df['State'].isin(['AL','AK','AZ','AR','FL','GA','ID','IN','IA','MD','MS','MO','NE','NH','ND','OH','OK','SC','TN','TX','UT','WV','WY']) ]
c_early
| Date | State | Cases | month | year | |
|---|---|---|---|---|---|
| 0 | 2020-01-01 | AK | 0 | Jan | 2020 |
| 1 | 2020-01-01 | AL | 0 | Jan | 2020 |
| 2 | 2020-01-01 | AR | 0 | Jan | 2020 |
| 3 | 2020-01-01 | AZ | 6 | Jan | 2020 |
| 9 | 2020-01-01 | FL | 0 | Jan | 2020 |
| ... | ... | ... | ... | ... | ... |
| 1368 | 2022-03-01 | TN | 3990080 | Mar | 2022 |
| 1369 | 2022-03-01 | TX | 13111654 | Mar | 2022 |
| 1370 | 2022-03-01 | UT | 1846721 | Mar | 2022 |
| 1375 | 2022-03-01 | WV | 981586 | Mar | 2022 |
| 1376 | 2022-03-01 | WY | 309818 | Mar | 2022 |
621 rows × 5 columns
#Select Rows
d_early = d_df[d_df['State'].isin(['AL','AK','AZ','AR','FL','GA','ID','IN','IA','MD','MS','MO','NE','NH','ND','OH','OK','SC','TN','TX','UT','WV','WY']) ]
d_early
| Date | State | Deaths | month | year | |
|---|---|---|---|---|---|
| 0 | 2020-01-01 | AK | 0 | Jan | 2020 |
| 1 | 2020-01-01 | AL | 0 | Jan | 2020 |
| 2 | 2020-01-01 | AR | 0 | Jan | 2020 |
| 3 | 2020-01-01 | AZ | 0 | Jan | 2020 |
| 9 | 2020-01-01 | FL | 0 | Jan | 2020 |
| ... | ... | ... | ... | ... | ... |
| 1368 | 2022-03-01 | TN | 47962 | Mar | 2022 |
| 1369 | 2022-03-01 | TX | 167798 | Mar | 2022 |
| 1370 | 2022-03-01 | UT | 8853 | Mar | 2022 |
| 1375 | 2022-03-01 | WV | 12720 | Mar | 2022 |
| 1376 | 2022-03-01 | WY | 3482 | Mar | 2022 |
621 rows × 5 columns
#Select specific months
c_early_df = c_early[c_early['month'].isin(['Jun','Jul','Aug','Sep','Oct']) ]
d_early_df = d_early[d_early['month'].isin(['Jun','Jul','Aug','Sep','Oct']) ]
c_early_df
| Date | State | Cases | month | year | |
|---|---|---|---|---|---|
| 255 | 2020-06-01 | AK | 21232 | Jun | 2020 |
| 256 | 2020-06-01 | AL | 795489 | Jun | 2020 |
| 257 | 2020-06-01 | AR | 402084 | Jun | 2020 |
| 258 | 2020-06-01 | AZ | 1292313 | Jun | 2020 |
| 264 | 2020-06-01 | FL | 2637713 | Jun | 2020 |
| ... | ... | ... | ... | ... | ... |
| 1113 | 2021-10-01 | TN | 39069931 | Oct | 2021 |
| 1114 | 2021-10-01 | TX | 128680099 | Oct | 2021 |
| 1115 | 2021-10-01 | UT | 16424825 | Oct | 2021 |
| 1120 | 2021-10-01 | WV | 7992616 | Oct | 2021 |
| 1121 | 2021-10-01 | WY | 3014173 | Oct | 2021 |
230 rows × 5 columns
d_early_df
| Date | State | Deaths | month | year | |
|---|---|---|---|---|---|
| 255 | 2020-06-01 | AK | 354 | Jun | 2020 |
| 256 | 2020-06-01 | AL | 23622 | Jun | 2020 |
| 257 | 2020-06-01 | AR | 5861 | Jun | 2020 |
| 258 | 2020-06-01 | AZ | 37242 | Jun | 2020 |
| 264 | 2020-06-01 | FL | 89621 | Jun | 2020 |
| ... | ... | ... | ... | ... | ... |
| 1113 | 2021-10-01 | TN | 490703 | Oct | 2021 |
| 1114 | 2021-10-01 | TX | 2120540 | Oct | 2021 |
| 1115 | 2021-10-01 | UT | 95057 | Oct | 2021 |
| 1120 | 2021-10-01 | WV | 126519 | Oct | 2021 |
| 1121 | 2021-10-01 | WY | 33892 | Oct | 2021 |
230 rows × 5 columns
c_early_df1 = c_early_df[c_early_df['year'].isin([2021]) ]
d_early_df1 = d_early_df[d_early_df['year'].isin([2021]) ]
fig = px.line(c_early_df1, x="month", y="Cases", color='State', title='Total Confirmed Cases')
fig.show()
fig = px.line(d_early_df1, x="month", y="Deaths", color='State', title='Total Death Cases')
fig.show()
plot_daywise_line('Deaths / 100 Cases', dth)